Previously, I worked at a clinical cancer diagnostics startup, where I developed computational infrastructure and applied machine learning algorithms for genetic testing based on DNA sequencing.
During my Master's degree at Stanford, where I was funded by the NSF GRFP Fellowship, I worked on machine learning for predictive modeling of gene expression.
During my undergraduate studies in at UC Berkeley, I worked with Pieter Abbeel on probabilistic and optimization techniques for household robotics.

I am interested in developing programming languages, software systems, user interfaces, algorithms, and theory that make it easier to construct, reason about, and use complex probabilistic computations.
I am also interested in probabilistic artificial intelligence and theories of cognition based on probabilistic reasoning.